Importing Essential Libraries

Train Test Split

Results for root mean squared error as scoring method

Without Parameter Tuning

R2 Score is : 0.8079437582298994

Mean Squared Error is : 91.58713188596205

Root Mean Squared Error is : 9.570116607751551

Mean Absolute Error is : 6.766035515770487

With Parameter Tuning

R2 Score is : 0.8071561848207268

Mean Squared Error is : 91.96270723321955

Root Mean Squared Error is : 9.589718829726946

Mean Absolute Error is : 6.844903688846095


Results for R2 Score as scoring method

Without Parameter Tuning

R2 Score is : 0.8079437582298994

Mean Squared Error is : 91.58713188596205

Root Mean Squared Error is : 9.570116607751551

Mean Absolute Error is : 6.766035515770487

With Parameter Tuning

R2 Score is : 0.808434817891743

Mean Squared Error is : 91.35295701302573

Root Mean Squared Error is : 9.557874084388523

Mean Absolute Error is : 6.804451638059193


Results for R2 Score as scoring method with n_iters 50, cv 10

On IBM Watson Studio with n_iters 50, cv 10

R2 Score is : 0.8101521044031971

Mean Squared Error is : 90.53402322175225

Root Mean Squared Error is : 9.51493684801703

Mean Absolute Error is : 6.76631248706134

On Local Machine (This Notebook)

Without Tuning

R2 Score is : 0.8079437582298994

Mean Squared Error is : 91.58713188596205

Root Mean Squared Error is : 9.570116607751551

Mean Absolute Error is : 6.766035515770487

With Tuning

R2 Score is : 0.808446954003891

Mean Squared Error is : 91.34716958485556

Root Mean Squared Error is : 9.557571322509478

Mean Absolute Error is : 6.813602463109473


Further parameter optimizations should give us better accuracy